Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis.

ABSTRACT:

Objective

To identify CT-acquisition parameters accounting for radiomics variability and to develop a post-acquisition CT-image correction method to reduce variability and improve radiomics classification in both phantom and clinical applications.

Methods

CT-acquisition protocols were prospectively tested in a phantom. The multi-centric retrospective clinical study included CT scans of patients with colorectal/renal cancer liver metastases. Ninety-three radiomics features of first order and texture were extracted. Intraclass correlation coefficients (ICCs) between CT-acquisition protocols were evaluated to define sources of variability. Voxel size, ComBat, and singular value decomposition (SVD) compensation methods were explored for reducing the radiomics variability. The nu

SUBMITTER: Ligero M 

PROVIDER: S-EPMC7880962 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature